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learns auditory information. Methodologically, the project will explore the integration of information-theoretic decompositions, deep neural architectures, and large language models (LLMs) as powerful
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of automatically predicting the veracity of textual claims using machine learning methods, while also producing explanations about how the model arrived at the prediction. Automatic fact checking methods often use
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key to revealing how the brain tracks, processes, and learns auditory information. Methodologically, the project will explore the integration of information-theoretic decompositions, deep neural
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Atanasova with a focus on researching methods for tasks that require a deep understanding of language, as opposed to shallow processing. We are interested in core methodology research on, among others
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deep learning, preferably including some exposure to graph neural networks or geometric deep learning. Proven experience with implementing machine learning methods in Python and Pytorch. Familiarity with
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Computer Vision There is growing trend towards explainable AI (XAI) today. Opaque-box models with deep learning (DL) offer high accuracy but are not explainable due to which there can be problems in
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Business School are available at www.cbs.dk/en . Closing date: 15 October 2025. Apply online CBS is a globally recognised business school with deep roots in the Nordic socio-economic model. Our faculty has a
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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and
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consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user